As the frequency of supply chain disruptions — from labour issues, trade wars, geopolitical conflicts, and climate impacts — rises to unprecedented levels, it is more important than ever for supply chains to be agile and resilient.

Operations leaders across all industries face market volatility and shifting customer demand. This environment increasingly exposes the limitations of traditional supply chain designs, planning, and risk and issue management approaches.

AI-driven decision intelligence helps organizations build more resilient supply chains by using a structured framework to unlock value and mitigate the negative impact of exceptions.

The current picture: Risks, costs, and disruptions

Recent global disruptions have forced companies to reconfigure their supply chains to adapt to new challenges. Organizations have injected agility, resiliency, and flexibility by increasing the diversification of suppliers, service providers, and product flows to create a more dynamic supply chain. However, this has also added risks, costs, and complexity, straining leaders’ ability to manage their operations and services effectively.

As supply chain exceptions increase, many organizations have become overwhelmed, leaving them unable to respond effectively. This, in turn, has led companies to remove resilient measures to reduce complexity or lean on traditional risk mitigation measures such as increasing inventory.

Many companies feel they are falling behind, a situation highlighted by Deloitte’s Global Chief Procurement Officer (CPO) survey.

The CPO view: Concerns around complexities and supplier resilience

Deloitte’s latest Global Chief Procurement Officer (CPO) survey highlights gaps in preparedness:

• 38% of executives are concerned about internal complexities in their supply chains
• 49% are anxious about supplier resilience
• 78% named operational efficiency as a top priority

Addressing these concerns and mitigating increased risks and disruptions can lead to significant costs: companies have seen labour costs rise further exacerbated by reshoring or near-shoring of manufacturing. Furthermore, since 2020, U.S. inventory levels have increased 40%, tying up capital and increasing warehousing costs.¹

In the face of uniquely challenging and costly times, what can operations leaders do to better prepare?

The answer: AI-driven decision intelligence

Many companies have implemented measures to address disruptions, including reshoring strategies and diversifying suppliers, service providers, and countries of origin. To support these efforts, companies are leveraging real-time visibility platforms and digital twins (virtual models of physical assets) but sustaining and expanding these strategies remains challenging.

To compete, companies should resist the temptation to revert solely to transactional efficiency. This way of thinking is no longer synonymous with the optimal and lowest-cost supply chain because of the increased external volatility and uncertainty affecting operations. Organizations should maintain agile and resilient measures and enhance them by integrating AI-driven decision intelligence to make supply chain operations more effective, robust, and responsive.

AI-driven decision intelligence helps organizations build agility and resilience into their supply chains while preserving efficiency, service levels, and overall financial performance.

How AI takes supply chains to the next level

Productivity gains and capabilities enabled by AI over the next decade are expected to increase global GDP by almost US$7 trillion, and many companies are already seeing success.

In 2022, Deloitte played a key role in AI implementation for Singapore-based Ocean Network Express (ONE), one of the world’s largest container shipping fleets. Working with Google Cloud, Deloitte helped ONE integrate advanced AI and analytics solutions to optimize operations and drive technological transformation.²

Global shipping and logistics company Maersk adopted AI decision support systems for terminal operations and route optimization, helping to streamline repetitive tasks and data gathering. This allowed staff to make quicker decisions, reduce human error and operational risk, and improve cost efficiency.

These examples demonstrate AI’s power, but its use extends beyond just smarter supply chain predictions—it’s about reengineering how organizations sense, decide, and act related to supply chain risk and disruptions.

AI enables predictive risk sensing, helping organizations avoid disruptions by providing the lead time to adjust strategic sourcing and planning decisions. These tools boost productivity and free managers and staff to improve processes and deliver business value rather than “fight fires.”

The future of supply chains depends on end-to-end visibility, enabled by inputs from digitally equipped operations and AI. This visibility provides leading companies with the tools to compete in the new reality of global supply chains.

Discover Deloitte’s Control Tower framework

Deloitte’s Control Tower framework for centralized supply chain visibility and management exemplifies AI-driven decision intelligence in action and shows how organizations can mature their supply chain data capabilities.

In stage six of the framework, the recommendation engine uses AI to present options for addressing issues and risks. Importantly, this stage does not remove humans from the decision-making process. Instead, it offers assessments of feasible and cost-efficient recommendations to support human judgment.

The system proactively pushes recommendations to users, enabling more informed decisions to improve the response velocity and value. Over time, it learns from results and uses them to drive further process improvements.

This capability can lead to end-to-end decision-making within the system, including autonomous write-back to source systems to execute the recommendation automatically and manage relevant communications and workflows to stakeholders.

Through the Control Tower framework, we are pushing the evolution of AI in supply chain management beyond providing options to automating full decision-making processes.

Real-world AI-driven decision intelligence application: J.D. Irving (JDI)

Deloitte worked with J.D. Irving, a diversified, vertically integrated conglomerate, on a transformative AI project powered by real-time transactional data, external data sources, and AI capabilities. The project enhances decision-making in procurement, processing, inventory, and fulfillment, and will improve efficiency by 20% through waste reduction and raw material optimization, thereby increasing customer satisfaction.³

Our collaboration has helped J.D. Irving leverage AI-driven decision intelligence to access real-time optimization recommendations, forecast issues, and improve supply chain operations⁴. The implementation of AI to enhance decision making has streamlined operations, broken down functional silos, and driven improvements in JDI’s operational performance.

Ready to build a resilient supply chain?

Deloitte’s advanced AI-driven frameworks and deep industry knowledge help organizations achieve significant efficiency gains and risk reduction, enabling people to focus on higher value work such as continuous improvement and growth initiatives versus managing transactional issues.

Don’t wait for the next disruption. Now is the time to embrace AI-driven decision intelligence to make your supply chain more agile, resilient, and efficient.